Understanding the importance of data quality

Most business leaders understand their data needs at work, but they often fail to prioritize their governance strategies, reported the Harvard Business Review. However, an increasingly reliance on the insight gleaned from this information has led many executives to place greater importance on understanding what constitutes poor data quality and how it can affect their companies.

While there are tangible costs associated with poor data - a 3 percent error rate translates to approximately 30 percent in non-value-added work costs - there are other intangible expenses, the source points out. Companies can quickly lose clients' trust or forfeit new business opportunities if they use inaccurate data.

"A more fundamental problem is that data can have many uses," Malcolm Chisholm told Information Management. "If we think data quality is 'fitness for use,' then data quality must be assessed independently for each use we put it to."

Some decision makers may also incorrectly assess the importance of data because they don't understand how it differs from information, contributor Jim Harris wrote in a recent article for the Obsessive-Compulsive Data Quality blog. Harris likens data to a potato, while information is like a tater tot - something that can made out of data, if analysts can interpret it accurately.